|Version 73 (modified by 2 years ago) (diff),|
Currently in progress
- http://south.aeracode.org/ (Current)--(De facto standard)
- https://github.com/paltman/nashvegas/ (Current)--(SQL focused for efficiency)
- https://github.com/keredson/deseb/ (Little activity)
- http://code.google.com/p/django-evolution/ (Current)
http://code.google.com/p/dmigrations/(Mar 02, 2009)--(MySQL Only) http://code.google.com/p/yadsel (Apr 12, 2008)(Very little activity) http://code.google.com/p/schema-evolution/(looks dead) http://code.google.com/p/django-schemaevolution/(Google Code Project closed) http://smileychris.tactful.co.nz/ramblings/dbevolution/(only alpha, discontinued in favor of django-evolution) aino-mutations
Dates shown are last activity publicly recorded on the project as at February 12, 2011.
Note: Most Django installations are using South these days. The below analysis was written before South became predominant.
Schema migration is one of those "hard" problems that I think will be impossible to get right for all the cases. What follows are my thoughts on how to get as close as possible in Django.
(please leave comments at the bottom and not inline to the proposal! Also, please add your name or some handle after the comment; everybody using "I" and then not identifying themselves is terribly unclear.)
A few bits of prior arts I examined.
- Alice has a blog application written in Django. A blog entry looks
class Entry(models.Model): title = models.CharField(max_length=30) body = models.TextField()After using this to write some blog entries, she realizes that she really should have had a publish date field on her model, and she wants to add one. Alice doesn't particularly care about old entries; she just wants them to have an empty publish date. She knows just enough SQL to understand how relational databases work, but that's about it.
- Ben has a simple ticket tracker with a ticket class that contains::
class Ticket(models.Model): reporter = models.EmailField() owner = models.EmailField() status = models.IntegerField(choices=STATUS_CHOICES) description = models.TextField()After two years of use, Ben wants to add product information to his ticket tracker and has decided he doesn't care about who reported a ticket, so
- he writes these models
class Product(models.Model): ... class Ticket(models.Model): reporter = models.EmailField() owner = models.EmailField() status = models.IntegerField(choices=STATUS_CHOICES) description = models.TextField() product = models.ForeignKey(Product)Ben knows quite a bit of SQL; he's also the company DBA.
- Carol supports a newsroom with a set of models that look like::
class Reporter(models.Model): ... class Article(models.Model): reporter = models.ForeignKey(Reporter) ... class Section(models.Model): stories = models.ManyToManyField(Article) ...As it turns out, her conception of
was naive, and on top of that she wants to separate certain types of articles into multiple
- classes. She rewrites her models to look like
class Reporter(models.Model): ... class Category(models.Model): ... class Article(models.Model): reporter = models.ForeignKey(Reporter) categories = models.ManyToManyField(Category) ... class Obituary(models.Model): ... class WeddingAnnouncement(models.Model): ... class Section(models.Model): included_categories = models.ManyToManyField(Category) ...Carol obviously needs to keep all the data in her system. Some articles will need to be moved into
, objects. Additionally, stories will be assigned categories from a mapping given to her by the web editor since the direct mapping has been removed. To add to the fun, Carol has 7 different news sites with separate databases using this system. Three of those systems run MySQL, the other four run PostgreSQL. Carol is a very experienced developer; she's been doing this web thing for almost ten years now.
1. Write SQL
This is the current situation: you write a bunch of SQL and bung it into your interactive interpreter.
Alice is a simple enough case that she shouldn't have to know SQL to make this work.
This situation sounds good to Ben: it's just two lines of SQL.
Carol would have to apply this SQL against 7 different databases (which is a waste of time), and she'd still have to write a bunch of Python code to deal with the data migration.
2. Automatic db introspection
In this scenario, Django inspects your models and your database, and outputs the SQL for adding/removing fields. You're supposed to inspect the SQL and then stick it into your database using something like::
$ ./manage.py sqlupdate | psql mydb
This works for Alice; she does
django-admin sqlupdate | mysql mydb
and is happy. However, if the SQL that Django put out happened to have a mistake in it, she might not have noticed, and could have lost some data.
Ben loves this situation; it does his two lines of SQL automatically, and he can poke at what's put out to make sure it's right for him. Except if he's using sqlite, which doesn't have a real ALTER statement, it's going to be a ton of work.
This doesn't really help Carol. Although the SQL that is put out is a start, it doesn't really get her very far. She still has to write a bunch of data migration by hand, and she also has no way of applying the SQL she writes quickly.
3. Automatically applied migration code
In this scenario, you give your models a version. When it comes time to upgrade,
you write a "upgrade-to-version-3" script and increment your version number.
When you run a
command (probably the newly-added
Django notices that you've added an upgrade script and runs it automatically.
This type of system comes in two (not necessarily exclusive) flavors:
- SQL only, where your upgrade scripts are in SQL.
- ActiveRecord Migration style, where you write your migrations in Python (which gets converted to SQL for you).
Each situation also could support symmetric migration (where you provide both an upgrade and a downgrade script).
Alice doesn't like the SQL flavor at all (she wants to use Python!). The Pythonic one works very well for her since the syntax mirrors other parts of Django she's familiar with. However, she'd prefer something like the automatic solution since it would save her from having to type anything at all.
Ben really likes this one; the SQL is still easy to write, and it gets into SVN so he can track his upgrades.
Carol loves this one. She can write custom SQL/Python that takes care of all the situation she needs. The Python option is a better fit for her since she has lots of custom code she needs to run.
4. Introspection + migration
This approach is a combination of
Automatic db introspection_ and
Automatically applied migration code_ -- one command produces a migration
script, you tickle your version number, and the
runs the migrations.
This works very well for Alice, and she gets the added bonus of having nice migrations stored for future inspection.
This is Ben's favorite option.
Carol's indifferent about this as opposed to the previous one: it helps slightly, but not all that much, really.
- "Just write SQL" sucks and is obviously wrong and needs to be fixed.
- DB introspection only goes so far, and doesn't give any way to extend what comes out beyond "just write SQL".
- Migration code works pretty well -- which is obvious if you look at how successful Rails has been with the feature http://api.rubyonrails.org/classes/ActiveRecord/Migration.html. The Python flavor is obviously more powerful, but for some uses SQL works well.
- Introspection + migration seems to be best-of-breed; it even has the added bonus of getting Alice to save her migrations in source control.
Given all the above, here's how I think schema evolution should work in Django:
- An optional module,
- way to store versions in the database
class ModelVersion(models.Model): content_type = models.ForeignKey(ContentType) version = models.PositiveIntegerField()This makes evolution optional and thus doesn't clutter up your tablespace if you don't need it.
- Models grow a
class MyModel(models.Model): ... class Meta: version = 3
applies evolutions using the following steps:
- Makes sure evolution is installed before proceeding.
- For each content type, checks that the version in the database matches the version in defined in the model. For those that don't match...
- Django looks for evolutions in
. Evolutions can either be SQL scripts named
or Python scripts named
will contain utilities to abstract evolution for different db backends. This exact API is TBD.
- For SQL evolutions, if a file named
will expect the output of the evolution to match the text file EXACTLY. If any differences happen, the transaction will be rolled back (for that reason SQL evolution scripts must not contain BEGIN/COMMIT).
(or somesuch) will inspect the database and pump out SQL evolution scripts into the right place in the app package(s). Users will then upgrade the version number and run
- Models grow a
Asked by nwp in the chat room: "what are the rules for checking whether you are in a position to apply to_version_X?"
Given a model that defines
version = 6
and a version of 3 stored in the database,
will be applied -- but only if they exist (missing files are OK).
If versions are stored per-model, what happens if evolutions affect multiple models, or create or delete them? For example, in Carol's situation above, how would the individual migration scripts cooperate to move the data around in the required way? I think versions make more sense on a per-app basis; if that distinction exists in magic-removal.
More discussion in a django-developers thread (should main points be copied here?).
: I added a proposal here at SchemaEvolutionProposal.]
Something Completely Different
I'd like to suggest a different approach altogether. This is, I think, orthogonal to the version management part of the existing proposals. Call this the DatabaseRefactoring view of schema evolution. For background, let me suggest a few starting points:
- Fowler and Sadalage's paper Evolutionary Database Design
- The Process of Database Refactoring from Scott Ambler's agiledata site, which leads to the online catalog of refactorings
- and of course there's Ambler and Sandalage's book, Refactoring Databases
I think there are several important advantages to this approach as compared to the one already suggested. For one thing, the smaller steps it takes are likely to be much more automatable. Sure, in some cases you'll have to write conversion code, but a lot of changes shouldn't require this. If you're evolving your application by (in part) refactorings, then there's an obviously good match (object refactorings map to database refactorings).
Why something different
I agree with "Something Completely Different" above. I worked on a Java-based product that used a similar approach to numbered schema versioning (although we worked with serialized objects in the backend instead of a relational DB). We had trouble merging changes with conflicting version numbers. This was not initially a huge problem for us, because we had very little overlap within and between our projects. However, the times that it happened it was a big deal, and as soon as we started real parallel development, it became a critical issue. I think for Django teams this is a killer, because deployments are so quite common and testing tends to be a part of the developers roles.
An example is svnA user creates schema version 5, while concurrently svnB makes version 5. Everything is fine until merge, then either user has an unusable database. This is bad enough, but consider branches! It gets ugly, and can easily break the production database at unexpected times.
Handling concurrent development -- multiple users and branches
Concurrent development requires communication, especially with a shared data store like the database. The above example should never break the production database -- if two developers commit conflicting code, it's up to them to work out the conflict. Preventing the conflicting code from reaching production is an organizational policy issue, not a web framework issue.
You do raise a good point regarding concurrent development with branches. It's still not possible to get rid of communication -- when it comes time to do a branch merge, discussing database schema will be mandatory. However, the tool should allow for branch merges; why not store a branch name AND a version number for each schema revision? When planning for a branch merge, one can implement a "from branch 1 version 6 to branch 2 version 3" migration. Obviously, migration points will need to be well defined, but supporting branches at least allows for the possibility.
Another way to concurrent development -- migrations as distributed version control systems
One of the issues with data base migrations, one raised by the previous section and one which has often bitten users of Rails migrations, is that they don't scale with the number of users: while rails-like migrations are wonderful for single users or very small teams (up to 3 or so members), the point is soon reached when different programmers will create different migrations with the same version number, and hell ensues (manual merges/renames of some of the migrations etc...).
The main problem of Rails' migration scheme versioning is, in fact, that they took a Centralized VCS scheme and applied it to a Decentralized VCS situation. Version numbers / revision numbers come from the worlds of CVS, SVN and the like where a central authority (the repository/VCS server) has the role of handling these version / revision numbers out and is the only entity allowed to issue these numbers. This central entity thus forces synchronization and updates (forbids the creation of version n+2 if you were using a version <= n, prevents the creation of version n+1 from version n when version n+1 already exists, ...).
As any user of the migration tool can create a new migration without having to ask a central authority, two users can create the same migration, or different migrations with the same version number, and the tool breaks down where it's sorely needed.
Since the problem has already been solved, this should be handled by learning from the various decentralized VCS (darcs, Git, Mercurial, Bazaar) and introducing one of their patch-merging and diff-tracking strategies into the migration tool. Of course this wouldn't necessarily resolve all the issues of incompatible migrations, but conflicting ones could at least be tracked.
Automatic interactive db introspection that generates migration scripts
I think that the nicest way for the user that would work for 99% of the cases is an automatic and (if needed) interactive command, that will generate the migration steps it took and store them in some script. Also, it could automatically update the version number in the suggestion on migration scripts above. So for a model that changes from::
class Ticket(models.Model): reporter = models.EmailField() owner = models.EmailField() stat = models.IntegerField(choices=STATUS_CHOICES)
class Ticket(models.Model): reporter = models.EmailField() status = models.IntegerField(choices=STATUS_CHOICES) description = models.TextField()
This is one removed field (owner), one added field (description), and one renamed field (stat->status). The renamed is the trickiest one obviously since it looks like one has been deleted and another added. So in this case the user should be given the menu::
The following fields are new: 1 status 2 description The following fields are not present any longer: 3 stat 4 owner Are any of these fields a rename? [y/N] y Which pair is coupled? 1, 3 The following fields are new: 1 description The following fields are not present any longer: 2 owner Are any of these fields a rename? [y/N] n Warning: removing the field owner will permanently delete data. Write "delete" and press enter to continue: delete Database update complete. Modifications written to Ticket-migration-1.sql
If there are only additions, then the entire menu can be totally skipped and just the additions added. If there are no renames the entire thing also becomes much shorter. I think this covers most cases, and any other cases can be handled manually by writing custom SQL migration scripts as above.
Anders Hovmöller (boxed@…)
A way to generate base sql migrations would fit very nicely, but automatically running them seems to be a problem. There are so many things that you have to take into consideration which Django simply can't do at present (for example, changing the type of a column that is used in a view). The best way I can see is to generate basic sql migration scripts which the developer can review before they are applied. This approach would go very well with the DbMigration project (
http://www.aswmc.com/dbmigration/ - url has no such project).
Mike H (mike@…)
You can't handle stupidity
To be honest I would not like a system that tried to cater to Carol. She is an idiot and needs to learn more. If the answer to something is "you don't have to know what you are doing" then it's not a good answer. Django.. to use Django, it's not that you don't have to know a lot, it's that you have less work to do. Everything is faster, not stupider.
Really I'm uncomfortable catering to Alice either. If she can't read SQL, tell her not to use a database. I say start off with a system that would only cater to a know-it-all like Ben. If you can layer on ways to handle Alice/Carol later then fine do it.. but please please do not take any power or functionality away from Ben in the process.
Also, versioning of database structure should not be the job of Django at all. If someone wants to version their DB structure they can bust out SVN, put Django's sql output commands to use and do it themselves. Django has no business versioning anything.
--Rob C (rtconner)
Are we going to stoop to the level of insulting hypothetical persons? :P Seriously though, Carol is not an idiot, she did the proper thing and designed what she needed what she needed when she needed it, and then changed it when that was required. This is just competent programming. Furthermore, I don't see why schema migration should be some magic fairyland object that has to be kept outside Django. Django handles databases, python is a language where you can change classes easily, and then having a system where changing some specific classes is quite a pain (like django currently) gives a kind of schizophrenic user experience.
In short: Schema evolution is a part of pretty much every django developers job and should be treated with the same attitude of "let's make things non-painful" as everything else. In the case of Carol she has to write some custom code for migration though, that's inevitable. -- Anders Hovmöller
Since I am not familiar with the suggestion on database refactoring I will only comment on the evolutionary versioning approach being debated. I have been working with relational databases for more than 30 years. SQL is fine, but whey force anyone to learn it if they don't already know it or don't want to? Otherwise why does Django provide automatic Model to SQL translation for everything from initial table creation to record entries, reads, etc.? I prefer the approach of providing a script or method that defines the changes from one version of a model to the next. It would be nice to have an automated introspection tool to create a first pass at this that I can edit to be absolutely correct and then have a tool that applies the intended changes so I do not have to generate the SQL and it will work no matter what database server I am using. This approach seems MUCH easier then Rails. It's also pretty much a requirement to automate and simplify updates to existing deployed apps. For those that love SQL, create a 2nd or optional alternative to the scripting/method approach alows the SQLphiles to use SQL. In much the same way that Django has a variety of parameters when defining Forms or Models to control Unique, Blank, etc. I can see a similar approach in version that defines how to translate a field from a prior version to the current version and if it's simply a name change, it would work the same way. The prior column name would be changed to the new one, the data would not be translated and all will be right with the world. It would be nice for the tool that runs the evolution method to check for data translation incompatibilities so we wont hurt ourselves too badly. If this description was not clear, please say so because the solution seems clear and obvious to me. --Jack Oswald
For me the majority of time consuming database changes take place during initial development experimenting with different approaches. Most of the time this also means simply adding or changing fields. It would be great to make these changes in the simple manner of the "Automatic interactive db introspection that generates migration scripts" example above. It also seems to more closely fit the Python ethos of not getting sidetracked into the maze of doing all things for all people. As stated, it fits 99% of my needs. --David
Seems the South project (http://south.aeracode.org/) has pretty much exactly implemented what what I suggested above in this page. -- Anders Hovmöller
I agree with Anders Hovmöller, the type of thinking that Rob C presents belongs in another community. Django is about making things more pleasant to work with. Having to edit the schema constantly during testing is tedious and wastes time and could be handled efficiently by a SchemeEvolution system. I don't think Django would have to make it default, but if the schema change is basic there is no reason why it shouldn't behandled. I'm sorry Rob C if you pride yourself in having to write simple table edits in SQL, but Django is and always has been about allowing programmers to focus on what makes their program unique instead of having to be "hardcore" and waste time with essentially robotic tasks.
-- Chris Paolini
Instead of relying solely on syncdb, how about suppling another command like migratedb to help with DB migration? That way, this will be an added capability on top of syncdb.
That's not a good option --Rly'eh